Taper angle optimization of scarf repairs in carbon-epoxy laminates

The increasing use of Carbon-Fibre Reinforced Plastic (CFRP) laminates in high responsibility applications introduces an issue regarding their handling after damage. The availability of efficient repair methods is essential to restore the strength of the structure. The availability of accurate predictive tools for the repairs behaviour is also essential for the reduction of costs and time associated to extensive tests. This work reports on a numerical study of the tensile behaviour of three-dimensional (3D) adhesively-bonded scarf repairs in CFRP structures, using a ductile adhesive. The Finite Element (FE) analysis was performed in ABAQUS® and Cohesive Zone Models (CZM’s) was used for the simulation of damage in the adhesive layer. A parametric study was performed on two geometric parameters. The use of overlaminating plies covering the repaired region at the outer or both repair surfaces was also tested as an attempt to increase the repairs efficiency. The results allowed the proposal of design principles for repairing CFRP structures.

Optimal tuning of fractional controllers using genetic algorithms

This study addresses the optimization of fractional algorithms for the discrete-time control of linear and non-linear systems. The paper starts by analyzing the fundamentals of fractional control systems and genetic algorithms. In a second phase the paper evaluates the problem in an optimization perspective. The results demonstrate the feasibility of the evolutionary strategy and the adaptability to distinct types of systems.

Particle swarm optimization with fractional-order velocity

This paper proposes a novel method for controlling the convergence rate of a particle swarm optimization algorithm using fractional calculus (FC) concepts. The optimization is tested for several well-known functions and the relationship between the fractional order velocity and the convergence of the algorithm is observed. The FC demonstrates a potential for interpreting evolution of the algorithm and to control its convergence.

Calculation of fractional derivatives of noisy data with genetic algorithms

This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

Cournot competition between a non-profit firm and a for-profit firm with uncertainty

In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

An optimization approach for the job shop scheduling problem

This paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.

Fractional control of heat diffusion systems

The concept of differentiation and integration to non-integer order has its origins in the seventeen century. However, only in the second-half of the twenty century appeared the first applications related to the area of control theory. In this paper we consider the study of a heat diffusion system based on the application of the fractional calculus concepts. In this perspective, several control methodologies are investigated and compared. Simulations are presented assessing the performance of the proposed fractional-order algorithms.

Finite Element Analysis (FEA) applied to heat transfer optimization process of pultrusion die systems

The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

Numerical solution of a PDE system with non-linear steady state conditions that translates the air stripping pollutants removal

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Optimization of the Pultrusion process

Manufacturing processes need permanently to innovate and optimize because any can be susceptible to continuous improvement. Innovation and commitment to the development of these new solutions resulting from existing expertise and the continuing need to increase productivity, flexibility and ensuring the necessary quality of the manufactured products. To increase flexibility, it is necessary to significantly reduce set-up times and lead time in order to ensure the delivery of products ever faster. This objective can be achieved through a normalization of the pultrusion line elements. Implicitly, there is an increase of productivity by this way. This work is intended to optimize the pultrusion process of structural profiles. We consider all elements of the system from the storehouse of the fibers (rack) to the pultrusion die. Particular attention was devoted to (a) the guidance system of the fibers and webs, (b) the resin container where the fibers are impregnated, (c) standard plates positioning of the fibers towards the entrance to the spinneret and also (d) reviewed the whole process of assembling and fixing the die as well as its the heating system. With the implementation of these new systems was achieved a significant saving of time set-up and were clearly reduced the unit costs of production. Quality assurance was also increased.

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

The Port as a “Non Consensual” Organisation: An IC Management Perspective

This paper addresses a gap in the literature concerning the management of Intellectual Capital (IC) in a port, which is a network of independent organizations that act together in the provision of a set of services. As far as the authors are aware, this type of empirical context has been unexplored when regarding knowledge management or IC creation/destruction. Indeed, most research in IC still focus on individual firms, despite the more recent interest placed on the analysis of macro-level units such as regions or nations. In this study, we conceptualise the port as meta-organisation, which has the generic goal of economic development, both for itself and for the region where it is located. It provides us with a unique environment due to its complexity as an “organisation” composed by several organisations, connected by interdependency relationships and, typically, with no formal hierarchy. Accordingly, actors’ interests are not always aligned and in some situations their individual interests can be misaligned with the collective goals of the port. Moreover, besides having their own interests, port actors also have different sources of influence and different levels of power, which can impact on the port’s Collective Intellectual Capital (CIC). Consequently, the management of the port’s CIC can be crucial in order for its goals to be met. With this paper we intend to discuss how the network coordinator (the port authority) manages those complex relations of interest and power in order to develop collaboration and mitigate conflict, thus creating collective intellectual assets or avoiding intellectual liabilities that may emerge for the whole port. The fact that we are studying complex and dynamic processes, about which there is a lack of understanding, in a complex and atypical organisation, leads us to consider the case study as an appropriate method of research. Evidence presented in this study results from preliminary interviews and also from document analysis. Findings suggest that alignment of interests and actions, at both dyadic and networking levels, is critical to develop a context of collaboration/cooperation within the port community and, accordingly, the port coordinator should make use of different types of power in order to ensure that port’s goals are achieved.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.